- Ph.D. Electrical Engineering, Princeton University
- M.A. Electrical Engineering, Princeton University
- B.Sc. Electrical and Computer Engineering, Cornell University
- High-performance and energy-efficient heterogeneous architecture
- Energy harvesting for emerging computing devices
- Energy management for portable electronics
- Temperature-aware computing
- Advanced processor and system cooling designs and management
- Performance characterization, analysis and prediction
- High-performance and power-efficient memory designs
Carole-Jean Wu is an associate professor of computer science and engineering in the School of Computing, Informatics, and Decision Systems Engineering at Arizona State University (ASU). She is currently a research scientist with Facebook?s AI Infrastructure. She holds affiliated faculty appointments in EECE and in the Biodesign Center for Biocomputation, Security and Society at ASU. She is the associate director of the National Science Foundation I/UCRC Center for Embedded Systems. Before ASU, Wu held a number of industrial internship positions with Intel, IBM and Google. She is a senior member of both ACM and IEEE.
Wu works in the area of computer and system architectures. In particular, her research interests include high-performance and energy-efficient computer architecture through hardware heterogeneity, energy harvesting techniques for emerging computing devices, temperature and energy management for portable electronics, performance characterization, analysis and prediction, and memory subsystem designs. She is the recipient of the 2018 IEEE ITHERM Best Paper Award, the 2017 NSF CAREER Award, the 2017 IEEE Young Engineer of the Year Award, the 2014 IEEE Best of Computer Architecture Letter Award, the 2013 Science Foundation of Arizona Bisgrove Early Career Award, and the 2011-12 Intel Ph.D. Fellowship Award. Her research has been supported by both industry sources and the National Science Foundation.
Wu leads the MLPerf Edge Inference WG, a multi-industry benchmarking consortium for machine learning. She also serves on the Executive Committee of the IEEE Technical Committee on Computer Architecture (TCCA) and the Steering Committee of the IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS). She is the Program Chair for the 2018 IEEE International Symposium on Workload Characterization. Wu completed her master's and doctoral degrees in electrical engineering from Princeton University and received a bachelor's degree in electrical and computer engineering from Cornell University.